留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

破冰船柴电混合动力系统优化设计及敏感性分析

杜文龙 郭凤祥 陈俐

杜文龙, 郭凤祥, 陈俐. 破冰船柴电混合动力系统优化设计及敏感性分析[J]. 中国舰船研究, 2021, 17(X): 1–10 doi: 10.19693/j.issn.1673-3185.02260
引用本文: 杜文龙, 郭凤祥, 陈俐. 破冰船柴电混合动力系统优化设计及敏感性分析[J]. 中国舰船研究, 2021, 17(X): 1–10 doi: 10.19693/j.issn.1673-3185.02260
DU W L, GUO F X, CHEN L. Optimization design and sensitivity analysis of diesel/battery hybrid propulsion system for polar icebreaker[J]. Chinese Journal of Ship Research, 2021, 17(X): 1–10 doi: 10.19693/j.issn.1673-3185.02260
Citation: DU W L, GUO F X, CHEN L. Optimization design and sensitivity analysis of diesel/battery hybrid propulsion system for polar icebreaker[J]. Chinese Journal of Ship Research, 2021, 17(X): 1–10 doi: 10.19693/j.issn.1673-3185.02260

破冰船柴电混合动力系统优化设计及敏感性分析

doi: 10.19693/j.issn.1673-3185.02260
基金项目: 国家工业和信息化部基金资助项目(G18473CZ04)
详细信息
    作者简介:

    杜文龙,男,1996年生,硕士生。研究方向:动力系统建模与优化。E-mail:duwenlong@sjtu.edu.cn

    陈俐,女,1973年生,博士,副教授。研究方向:动力系统优化与控制。E-mail:li.h.chen@sjtu.edu.cn

    通信作者:

    陈俐

  • 中图分类号: U664.16

Optimization design and sensitivity analysis of diesel/battery hybrid propulsion system for polar icebreaker

  • 摘要:   目的  针对极地破冰船的经济性和环保性要求,提出由柴油发电机组和储能电池组成的破冰船柴电混合动力系统。  方法  首先,基于冰载荷变化等级建立阻力模型,并采用反向建模法建立柴电混合动力系统的能量流模型;然后,以破冰船的年油耗量和生命周期总成本为优化目标,采用快速非支配排序遗传优化算法(NSGA-II)对动力系统设计参数进行优化,并基于优劣解距离法(TOPSIS)得到最优设计方案;最后,开展优化目标对7个设计参数的敏感性分析。  结果  仿真结果表明,柴电混合动力系统的最优设计方案比传统柴电推进系统节约了1.89%油耗,且纯电航行总里程占比为31.22%,但储能电池的引入降低了系统经济性。参数敏感性分析结果表明,2个优化目标对主机容量、电池组数量、电池荷电状态边界的敏感度较高,而对减速器减速比、电机转子体积和螺旋桨尺寸则相对不敏感。  结论  研究成果可为破冰船及柴电混合动力船舶的参数设计提供参考。
  • 图  1  动力系统架构示意图

    Figure  1.  Schematic diagram of propulsion system

    图  2  单次航行周期的航速与冰级

    Figure  2.  Speed and ice scale in single sailing cycle

    图  3  基准主机的SFOC图谱

    Figure  3.  SFOC map of the baseline diesel engine

    图  4  基准电机的效率图谱

    Figure  4.  Efficiency map of the baseline motor

    图  5  优化流程图

    Figure  5.  Optimization flow chart

    图  6  优化结果

    Figure  6.  Optimization results

    图  7  7个设计变量对两个目标函数的影响

    Figure  7.  The influence of seven design variables on the objectives

    表  1  破冰船单次航行周期工况

    Table  1.   Operating profile of the icebreaker in single sailing cycle

    时间段航速v/kn冰级时间段航速v/kn冰级
    第0~30天120第36~39天34
    第30~32天51第39~42天35
    第32~33天32第42~44天51
    第33~36天33第44~74天120
    下载: 导出CSV

    表  2  船舶尺寸及模型参数

    Table  2.   ship size and model parameters

    参数名称符号数值参数名称符号数值
    船宽/m B 22.3 推力系数因子1 ${K_{{T1} } }$ −0.224 6
    电池寿命/年 ${ {{B} }_{\rm{life} } }$ 5 推力系数因子2 ${K_{{T2} } }$ −0.411 2
    柴油机单位成本/(元·kW−1 ${c_{\rm{engine}}}$ 250 推力系数因子3 ${K_{{T3} } }$ 0.511 5
    电机单位成本/(元·kW−1 ${c_{\rm{motor}}}$ 32 船长/m L 122.5
    发电机单位成本/(元·kW−1 ${c_{\rm{g}}}$ 350 水线面船长/m ${L_{\rm{wl}}}$ 116
    冰浮阻力系数 ${C_{\rm{b}}}$ 0.5 破冰船总质量/kg M 1.4×106
    除冰阻力系数 ${C_{\rm{c}}}$ 1.11 螺旋桨数量 ${N_{\rm{P}}}$ 2
    破冰阻力系数 ${C_{\rm{r}}}$ 2.73 傅汝德数幂指数 p' 1.157
    吃水深度/m d 7.85 强度因子幂指数 q 1.54
    排水量/t DT 13 990 电池初始荷电量/% SOC0 95
    重力加速度/(m·s−2 g 9.8 基准柴油机排量/L ${V_{\rm{d0}}}$ 11.427
    锂电池年通货膨胀率 ${g_{\rm{bat}}}$ 0.03 基准电机转子体积/L ${V_{\rm{r0}}}$ 34.4
    运营成本的通货膨胀率 ${g_{\rm{ope}}}$ 0.03 破冰船运营总年限/年 Y 25
    年利息率 ${I_{\rm{a}}}$ 0.05 发电机效率 ${\eta _{\rm{gen}}}$ 0.97
    扭矩系数因子1 ${K_{{Q}1}}$ −0.046 6 冰密度/(kg·m−3 ${\rho _{i}}$ 880
    扭矩系数因子2 ${K_{{Q}2} }$ 0.005 9 海水密度/(kg·m−3 ${\rho _{\rm{w}}}$ 1.025×103
    扭矩系数因子3 ${K_{{Q}3} }$ 0.045
    下载: 导出CSV

    表  3  设计变量的变化范围

    Table  3.   variation range of design variables

    设计变量符号变化范围
    减速比 i 1~50
    主机排量/L ${{V}_{\rm{d}}}$ 1Vd0~6 Vd0
    电机转子体积/L ${{V}_{\rm{r}}}$ 1 Vr0~5 Vr0
    螺旋桨直径/m D 3~5
    电池包数量/个 $Nu{m_{\rm{b}}}$ 0~12 000
    最大荷电状态/% SOCmax 65~95
    最小荷电状态/% SOCmin 5~40
    下载: 导出CSV

    表  4  设计方案的仿真结果对比

    Table  4.   Comparison of simulation results of design schemes

    方案序号年油耗量/t生命周期总成本/元纯电航行总里程/h
    R3 098.836.050 6×107587.42
    Q3 172.144.003 6×1070
    B3 111.894.695 7×107554.53
    P3 171.84.003 3×1070
    下载: 导出CSV
  • [1] ZHANG Z H, HUISINGH D, SONG M L. Exploitation of trans-Arctic maritime transportation[J]. Journal of Cleaner Production, 2019, 212: 960–973. doi: 10.1016/j.jclepro.2018.12.070
    [2] PARSONS J, DINWOODIE J, ROE M. Northern opportunities: a strategic review of Canada's Arctic icebreaking services[J]. Marine Policy, 2011, 35(4): 549–556. doi: 10.1016/j.marpol.2011.01.017
    [3] LINDSTAD H, ESKELAND G S, PSARAFTIS H, et al. Maritime shipping and emissions: a three-layered, damage-based approach[J]. Ocean Engineering, 2015, 110: 94–101. doi: 10.1016/j.oceaneng.2015.09.029
    [4] AJIOKA Y, OHNO K. Electric propulsion systems for ships[J]. Hitachi Review, 2013, 62(3): 231–232.
    [5] YANG Y, ZHANG G C, TANG W Y, et al. Research of the optimal propulsion system for a polar scientific icebreaker[J]. Advanced Materials Research, 2011, 308-310: 477–482. doi: 10.4028/www.scientific.net/AMR.308-310.477
    [6] ZHU J Y, CHEN L, XIA L J, et al. Bi-objective optimal design of plug-in hybrid electric propulsion system for ships[J]. Energy, 2019, 177: 247–261. doi: 10.1016/j.energy.2019.04.079
    [7] 庞水, 杨楚平, 刘如磊, 等. 船舶微电网锂电池储能系统容量配置多目标优化方法[J]. 中国舰船研究, 2020, 15(6): 22–28.

    PANG S, YANG C P, LIU R L, et al. Multi-objective optimization method of energy storage system capacity allocation for marine microgrid lithium battery[J]. Chinese Journal of Ship Research, 2020, 15(6): 22–28 (in Chinese).
    [8] 李跃娟, 齐巍, 王成, 等. 并联混合动力汽车ECMS的时变等效因子提取算法的研究[J]. 汽车工程, 2021, 43(2): 181–188.

    LI Y J, QI W, WANG C, et al. Study on extraction algorithm for time-varying equivalent factor of ECMS for parallel hybrid electric vehicle[J]. Automotive Engineering, 2021, 43(2): 181–188 (in Chinese).
    [9] 谢强, 陈海龙, 章继峰. 极地航行船舶及海洋平台防冰和除冰技术研究进展[J]. 中国舰船研究, 2017, 12(1): 45–53. doi: 10.3969/j.issn.1673-3185.2017.01.008

    XIE Q, CHEN H L, ZHANG J F. Research progress of anti-icing/deicing technologies for polar ships and offshore platforms[J]. Chinese Journal of Ship Research, 2017, 12(1): 45–53 (in Chinese). doi: 10.3969/j.issn.1673-3185.2017.01.008
    [10] CAPASSO C, VENERI O. Experimental analysis on the performance of lithium based batteries for road full electric and hybrid vehicles[J]. Applied Energy, 2014, 136: 921–930. doi: 10.1016/j.apenergy.2014.04.013
    [11] BOSICH D, SULLIGOI G. Voltage control on a refitted luxury yacht using hybrid electric propulsion and LVDC distribution[C]//Proceedings of the 2013 8th International Conference and Exhibition on Ecological Vehicles and Renewable Energies (EVER). Monte Carlo, Monaco: IEEE, 2013: 1-6.
    [12] 刘中孝, 葛昊, 李哲, 等. 锂离子电池低温循环老化的空间分布与特征[J]. 汽车安全与节能学报, 2019, 10(4): 502–510. doi: 10.3969/j.issn.1674-8484.2019.04.012

    LIU Z X, GE H, LI Z, et al. Distribution and characteristics of degradation of lithium ion batteries cycled at low temperature[J]. Journal of Automotive Safety and Engergy, 2019, 10(4): 502–510 (in Chinese). doi: 10.3969/j.issn.1674-8484.2019.04.012
    [13] 马瑞骏, 窦银科, 裴玉晶, 等. 南极超低温环境下磷酸铁锂电池性能研究[J]. 电源技术, 2018, 42(12): 1786–1789. doi: 10.3969/j.issn.1002-087X.2018.12.007

    MA R J, DOU Y K, PEI Y J, et al. Study on the performance of lithium iron phosphate battery in low temperature environment in Antarctica[J]. Chinese Journal of Power Sources, 2018, 42(12): 1786–1789 (in Chinese). doi: 10.3969/j.issn.1002-087X.2018.12.007
    [14] GEERTSMA R D, NEGENBORN R R, VISSER K, et al. Design and control of hybrid power and propulsion systems for smart ships: a review of developments[J]. Applied Energy, 2017, 194: 30–54. doi: 10.1016/j.apenergy.2017.02.060
    [15] 王凯, 卢博闻, 李宇奇, 等. 船舶多清洁能源混合动力系统优化设计方法[J]. 船舶工程, 2020, 42(4): 8–14, 108.

    WANG K, LU B W, LI Y Q, et al. Optimization design method of marine multi-clean energy hybrid power system[J]. Ship Engineering, 2020, 42(4): 8–14, 108 (in Chinese).
    [16] 徐汉卿, 朱建钢, 薛怀平, 等. 雪龙号南北极考察走航图的制作[J]. 测绘科学, 2005, 30(6): 97–98. doi: 10.3771/j.issn.1009-2307.2005.06.034

    XU H Q, ZHU J G, XUE H P, et al. The tracking map of Xue Long in Antarctic and Arctic expedition[J]. Science of Surveying and Mapping, 2005, 30(6): 97–98 (in Chinese). doi: 10.3771/j.issn.1009-2307.2005.06.034
    [17] 刘源. 破冰船的冰阻力估算方法研究[D]. 武汉: 华中科技大学, 2014.

    LIU Y. Estimation and computation of ice-resistance for icebreaker[D]. Wuhan: Huazhong University of Science and Technology, 2014.
    [18] 齐江辉, 郭翔, 陈强, 等. 碎冰区航行船舶阻力预报数值模拟研究[J]. 兵器装备工程学报, 2019, 40(11): 207–212. doi: 10.11809/bqzbgcxb2019.11.041

    QI J H, GUO X, CHEN Q, et al. A numerical simulation research for resistance prediction of ship in crushed ice area[J]. Journal of Sichuan Ordnance, 2019, 40(11): 207–212 (in Chinese). doi: 10.11809/bqzbgcxb2019.11.041
    [19] SOLEYMANI M, YOOSOFI A, KANDI D M. Sizing and energy management of a medium hybrid electric boat[J]. Journal of Marine Science and Technology, 2015, 20(4): 739–751. doi: 10.1007/s00773-015-0327-0
    [20] RIZZONI G, GUZZELLA L, BAUMANN B M. Unified modeling of hybrid electric vehicle drivetrains[J]. IEEE/ASME Transactions on Mechatronics, 1999, 4(3): 246–257. doi: 10.1109/3516.789683
    [21] JOHNSON V H. Battery performance models in ADVISOR[J]. Journal of Power Sources, 2002, 110(2): 321–329. doi: 10.1016/S0378-7753(02)00194-5
    [22] XU L F, MUELLER C D, LI J Q, et al. Multi-objective component sizing based on optimal energy management strategy of fuel cell electric vehicles[J]. Applied Energy, 2015, 157: 664–674. doi: 10.1016/j.apenergy.2015.02.017
    [23] 罗述全. 传统优化算法与遗传算法的比较[J]. 湖北工业大学学报, 2007, 22(3): 32–35. doi: 10.3969/j.issn.1003-4684.2007.03.010

    LUO X Q. Comparision between readitional optimized algorithm and heredity algotithm[J]. Journal of Hubei University of Technology, 2007, 22(3): 32–35 (in Chinese). doi: 10.3969/j.issn.1003-4684.2007.03.010
    [24] 焦红伟. 几类非凸规划问题全局解的求解方法[D]. 西安: 西安电子科技大学, 2015.

    JIAO H W. Global optimization methods for solving several classes of nonconvex programming problems[D]. Xi'an : Xidian University, 2015.
    [25] ZHU J Y, CHEN L, WANG X F, et al. Bi-level optimal sizing and energy management of hybrid electric propulsion systems[J]. Applied Energy, 2020, 260: 114134. doi: 10.1016/j.apenergy.2019.114134
    [26] 蒋佩华, 华冰, 黄宇, 等. 基于遗传算法的变质量航天器姿态控制方法[J]. 郑州大学学报(工学版), 2019, 40(4): 1–7.

    JIANG P H, HUA B, HUANG Y, et al. The attitude control method of variable mass spacecraft based on genetic algorithm[J]. Journal of Zhengzhou University (Engineering Science), 2019, 40(4): 1–7 (in Chinese).
    [27] 朱天军, 胡伟, 王林. 基于特征选择遗传算法对混合动力汽车的研究[J]. 机械设计与制造, 2020(3): 85–89. doi: 10.3969/j.issn.1001-3997.2020.03.020

    ZHU T J, HU W, WANG L. Research on feature-based selection genetic algorithm for hybrid electric vehicle[J]. Machinery Design & Manufacture, 2020(3): 85–89 (in Chinese). doi: 10.3969/j.issn.1001-3997.2020.03.020
    [28] 段菲, 张利军, 陈鸽, 等. 基于多目标优化算法NSGA II的极地穿梭油轮型线设计[J]. 中国舰船研究, 2017, 12(6): 66–72. doi: 10.3969/j.issn.1673-3185.2017.06.010

    DUAN F, ZHANG L J, CHEN G, et al. Polar vessel hullform design based on the multi-objective optimization NSGA Ⅱ[J]. Chinese Journal of Ship Research, 2017, 12(6): 66–72 (in Chinese). doi: 10.3969/j.issn.1673-3185.2017.06.010
    [29] ZHU J Y, CHEN L, WANG B, et al. Optimal design of a hybrid electric propulsive system for an anchor handling tug supply vessel[J]. Applied Energy, 2018, 226: 423–436. doi: 10.1016/j.apenergy.2018.05.131
    [30] LAI Y J, LIU T Y, HWANG C L. TOPSIS for MODM[J]. European Journal of Operational Research, 1994, 76(3): 486–500. doi: 10.1016/0377-2217(94)90282-8
  • 加载中
图(7) / 表(4)
计量
  • 文章访问数:  26
  • HTML全文浏览量:  12
  • PDF下载量:  0
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-01-07
  • 修回日期:  2021-05-05
  • 网络出版日期:  2021-08-27

目录

    /

    返回文章
    返回